• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.60-65
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• 2017

In this study, a simplified FE model for evaluating seismic performance of valve support was suggested and an apparatus for a real structure testing was developed. The seismic performances of three different types of valve supports were evaluated by the real structure testing. By comparing the results between the real structure testing and FEA using the simplified FE model, it was verified that the suggested simplified FE model can be utilized for comparative evaluation of seismic performance of valve supports.

• Journal of Korean Society on Water Environment
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• v.20 no.2
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• pp.151-156
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• 2004

A decision support system, Watershed Analysis Risk Management Framework(WARMF), was applied to the Kyungan Stream watershed, a tributary of Lake Paldang, for calculation of total maximum daily loads(TMDL). The WARMF system was developed by Systech Engineering, USA, and has been successfully used in several watersheds, for TMDL studies. The study area was divided into 14 sub-basins, based on digital elevation model(DEM). The integrated watershed and stream model of WARMF was validated by flow and BOD data measured during the year of 1999. There were reasonable agreements between model results and field data, both in water flow and BOD. The validated Kyungan WARMF was extensively utilized to study the quantitative relationship between waste loads and receiving water quality. Based on TMDL guideline at Paldang Lake and Kyungan Stream, the water quality criterion were set to be 3.0mg/L, 3.5mg/L, and 4.0mg/L at the watershed outlet. The allowable waste loads of BOD, both from point and non-point sources, were determined at each water quality criterion. From this study, it was concluded that the WARMF provided several advantages over the conventional application of watershed and stream models for TMDL study, such as time variable simulations, multiple possible soutions, and reduction loads for goal water quality, etc.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• Journal of Korean Academy of Nursing
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• v.34 no.3
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• pp.541-551
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• 2004

Purpose: This study was to identify the effects of the predictive factors of Internet addiction and to develop a predictive model that explains Internet addiction among adolescents in Korea. Method: Data was collected from 664 adolescents in Puasan and Ulsan. Data analysis was done using the SPSS 10.0 Win Program for descriptive and correlational statistics and the LISREL 8.53 Win Program for Covariance structural analysis. Result: The fit of the hypothetical model to the data was moderate, it was modified by deleting four paths. Compared to the hypothetical model, the revised one had a better fit to the data($\chi^2$/df=6.50, GFI=.99, AGFI=.90, RMR=.02, NNFI=.88, NFI=.98, CN=279). Gender, friend support, and loneliness had significant direct effects on Internet addiction. The direct and indirect effect of self-esteem on Internet addiction was significant. The indirect effect of family support on Internet addiction was significant but its direct effect was insignificant. The direct and indirect effects of stress and impulsiveness on Internet addiction were significant but their total effects were insignificant. Conclusion: Finally, to decrease loneliness, and to increase family support and self-esteem, an effective intervention program and education should be developed to prevent Internet addiction of adolescents.

• Journal of Korean Academy of Nursing
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• v.47 no.1
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• pp.60-70
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• 2017

Purpose: This study was conducted to construct and test a structural equation model of health-related quality of life (HRQoL) among hospitalized patients with pulmonary tuberculosis (PTB). Methods: Participants were 256 patients with PTB who were 20 years or older and admitted in two national tuberculosis hospitals. The patients participated in pulmonary function testing and responded to structured questionaries. Results: The goodness-of-fit statistics of the final hypothetical model were as follows: ${\chi}^2/df=2.19$, RMSEA=.07, SRMR=.05, GFI=.95, NFI=.95, CFI=.96, TLI=.92, and PCFI=.52. Symptoms and general health perception had significant direct effects, and subjective economic status, social support and stigma had significant indirect effect on HRQoL of hospitalized patients with PTB. These variables explained 64% of variance in the prediction model. Conclusion: Findings suggest that strategies and intervention for physical symptoms and depressive symptoms are crucial to improve the quality of life in hospitalized patients with PTB. The development of various social support programs is also recommended.

• Korean Journal of Occupational Health Nursing
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• v.29 no.4
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• pp.262-272
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• 2020

Purpose: This study aims to investigate the degree of job demand, job resources, burnout, and the organizational commitment of administrative nurses based on the job demands-resources model. Further, it seeks to confirm the influencing factors affecting nurses' burnout and organizational commitment. Methods: The participants were 188 administrative nurses working at hospitals (one tertiary hospital and six general hospitals) located in D City. The collected data were analyzed with IBM SPSS Statistics 23.0 using frequency, percentage, mean, standard deviation, t-tests, ANOVA, Pearson's correlation coefficient, and multiple regression analysis. Results: The influential factors of burnout were role conflict (β=.50), job demand (β=.18), job position (β=-.17, team leaders and above), and social support (β=-.15). The regression model had an explanatory power of 59%. The influential factors of organizational commitment were appropriate rewards (β=.59), job position (β=.15, team leader or above), working department (β=.14, referral center and health screening administration department), and social support (β=.18). The regression model had an explanatory power of 59.5%. Conclusion: The results support the job demands-resources model, and interventions should be developed to decrease job demand and provide sufficient job resources.

• Journal of the Korean Home Economics Association
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• v.32 no.4
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• pp.193-208
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• 1994

This study investigated the causality of the children's self-perceived competence and related variables(age, sex, socio-demographic variables, family structure, the number of brother, home environmental process variables and peer group environmental variables.) The subjects of this study were 842 children at age five, seven, nine, eleven and thirteen attending kindergartens. elementary schools and junior high schools and their mothers in Seoul. This study employed children's self-perceived competence scales(The Pictorial scales for 5, 7, Qestionnaire for 9, 11, 13) home environment scales and peer group enviornment scales(the Pictorial scales for 5, 7 Qestionnaire for 9, 11, 13) Freqencies one way-ANOVA Pearson's Cronbach's αmultiple regression and path analysis were used for data-analysis. Major findings were as follows: 1. The results of the analysis of causal model showed that the variables that affected cognitive self-perceived competence directly were age, sex, parent's education economic status of the home the number of brother and peer's emotional support 2. The results of the analysis of causal model showed that the variables that affected social self-perceived competence directly were sex, economic status of the home, peer's emotional support and common activity. 3. The results of the analysis of causal model showed that the variables that affected physical self-perceived competence directly were age, sex, peer's emotional support and common activity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.592-595
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• 2009

In this paper, we propose a face detection technique for still pictures which sequentially uses a skin-color model and a support vector machine (SVM). SVM is a learning algorithm for solving the classification problem. Some studies on face detection have reported superior results of SVM over neural networks. The SVM method searches for a face in a picture while changing the size of the window. The detection accuracy and the processing time of SVM vary largely depending on the complexity of the background of the picture or the size of the face. Therefore, we apply a face candidate area detection method using a skin-color model as a preprocessing technique. We compared the method using SVM alone with that of the proposed method in respect to face detection accuracy and processing time. As a result, the proposed method showed improved processing time while maintaining a high recognition rate.

• Journal of Korean Biological Nursing Science
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• v.20 no.2
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• pp.84-91
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• 2018

Purpose: The purpose of this study was to construct and test a structural equation model to investigate the risk factors of metabolic syndrome in rural women. Methods: The raw data in this study was collected from the Korean Genome and Epidemiology Study supervised by the Korea Centers for Disease Control and Prevention from 2005 to 2010. The data included physical examinations and surveys of 1,125 women, who resided in three rural areas of South Korea. The structural model in this study was composed of five latent variables: depression, stress, social support, health behavior, and metabolic syndrome. The structural equation model was used to assess the relationships among the variables. Results: The results of the study showed that depression and stress had direct effects on metabolic syndrome. Social support had a direct effect on health behavior and metabolic syndrome. Also, health behavior had a direct effect on metabolic syndrome. Conclusion: This study may serve as a guideline for interventions and strategies used to reduce metabolic syndrome in rural women.

• Structural Engineering and Mechanics
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• v.28 no.6
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• pp.677-694
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• 2008

A vibration power minimization model is developed, based on the mobility matrix method, for a vibration isolation system consisting of a vibrating source placed on an elastic support structure through multiple resilient mounts. This model is applied to investigate the design optimization of an X-Y motion stage-based vibration isolation system used in semiconductor wire-bonding equipment. By varying the stiffness coefficients of the resilient mounts while constraining the dynamic displacement amplitudes of the X-Y motion stage, the total power flow from the X-Y motion stage (the vibrating source) to the equipment table (the elastic support structure) is minimized at each frequency interval in the concerned frequency range for different stiffnesses of the equipment table. The results show that when the equipment table is relatively flexible, the optimal design based on the proposed vibration power inimization model gives significantly little power flow than that obtained using a conventional vibration force minimization model at some critical frequencies. When the equipment table is rigid enough, both models provide almost the same predictions on the total power flow.